There is a method employing a multispectral image recorded with multi-wavelength light as a technique for grasping various pieces of information such as the kind, the material, and the state of an object in a captured scene with high precision. The behavior of light of each wavelength when the light is reflected on the surface of an object differs depending on the kind or the state of the object. Therefore, it is possible to grasp the kind or the state of an object by obtaining reflection characteristics of the object from observed spectra, which are observation values to be recorded at the respective pixels of the multispectral image.
However, it is difficult to accurately acquire object information from observed spectra. This is because observed spectra include characteristics of illumination light in addition to reflection characteristics of an object. Observed spectra to be recorded at the respective pixels of a multispectral image is a result obtained by capturing the light reflected on the surface of an object irradiated with illumination light by a sensor. Therefore, the observed spectra include characteristics of illumination light in addition to reflection characteristics of an object. The observed spectra vary by an influence of illumination light in the environment where illumination varies such as outdoors. It is impossible to accurately acquire object information even with use of the observed spectra as described above.
In order to accurately acquire object information, it is necessary to accurately acquire characteristics of illumination light at the time of capturing image, and to remove an influence of illumination at the time of capturing image from a multispectral image, in other words, to remove a portion representing characteristics of illumination light from the observed spectra. Hereinafter, characteristics of light expressed as a spectral configuration are referred to as spectral characteristics.
A method for directly measuring illumination light can be considered as one of the methods for acquiring spectral characteristics of illumination at the time of capturing image. In this method, however, it is necessary to configure a system, in which an image sensor and an illumination light measuring sensor are integrated, in addition to the necessity of separately installing a sensor for measuring illumination light. This method causes disadvantages such as a cost increase and system oversizing. Further, it is necessary to install the illumination light measuring sensor at the same place as where a measurement object is placed, or near the place where a measurement object is placed. Therefore, when the distance between a measurement object and an image sensor is far, as exemplified by ground observation from an airplane, the following drawbacks may occur. Specifically, it may be impossible to physically install an illumination light measuring sensor, or a large amount of labor or a large amount of cost may be required even if it is possible to install an illumination light measuring sensor.
In order to avoid these drawbacks, it is desired to estimate spectral characteristics of illumination only with use of information on an observed multispectral image.
There is a method employing information on a surface reflectance (spectral reflectance) of an object to be observed for each wavelength, as one of the methods for estimating spectral characteristics of illumination at the time of capturing image from multispectral image information (see e.g. PTL 1).
In the method described in PTL 1, a color temperature of illumination is estimated by correlating an area of illumination with points on a black body locus, and by calculating and optimizing the energy necessary for satisfying the following assumption while changing the color temperature. PTL 1 uses an assumption that a skin color area or a gray color area of an object is large within an observed scene. If the color temperature of illumination can be estimated, it is possible to estimate spectral characteristics of illumination light from the estimated color temperature.
In the method described in PTL 1, however, it is assumed that a spectral reflectance of an object to be observed can be expressed by using a model whose spectral reflectance is known, and spectral characteristics of illumination are estimated based on the assumption. Therefore, this method involves the following drawbacks. Specifically, a spectral reflectance of an object is a value unique to the object, which is determined by the material or a like property of the object. The value of spectral reflectance varies depending on an object to be observed. Therefore, the assumption that it is possible to express the spectral reflectance of an intended object to be observed by using a model whose spectral reflectance is known is not always useful. Thus, in the method based on the aforementioned assumption, it is not always possible to accurately estimate spectral characteristics of illumination with respect to an intended object to be observed.
In order to solve the aforementioned drawbacks, it is necessary to estimate spectral characteristics of illumination, without an assumption on a surface reflectance of an object. Several methods employing a dichromatic reflection model are proposed as the method for implementing the aforementioned idea (see e.g. NPL 1 and NPL 2).